Here is some good amazing zing zing…intro for u
Aaj kal diff devics r used for data.Here i am expliining aboyut forth week assign of practical machie lerning.I hope u unaderstaning all this cudeeee.
```r
v_1 <- read.csv("C:\\Users\\HP\\Downloads\\pml-training.csv", stringsAsFactors = F,na.strings = c("","NA","#DIV/0!"))
v_2 <- read.csv("C:\\Users\\HP\\Downloads\\pml-testing.csv", stringsAsFactors = F,na.strings = c("","NA","#DIV/0!"))
dim(v_1); dim(v_2)
```
```
## [1] 19622 160
```
```
## [1] 20 160
```
```r
#for reproducability
set.seed(101)
v_3 <- createDataPartition(v_1$classe, p = 0.8, list = F)
v_6 <- v_1[-v_3,]
v_1 <- v_1[v_3,]
dim(v_1); dim(v_6)
```
```
## [1] 15699 160
```
```
## [1] 3923 160
```
```r
table(v_1$classe)/nrow(v_1)
```
```
##
## A B C D E
## 0.2843493 0.1935155 0.1744060 0.1638958 0.1838334
```
```r
v_4 <- sapply(select(v_1,names(v_1)[grepl("_belt",names(v_1))]),
function(x) sum(is.na(x)))
v_4
```
```
## roll_belt pitch_belt yaw_belt
## 0 0 0
## total_accel_belt kurtosis_roll_belt kurtosis_picth_belt
## 0 15396 15413
## kurtosis_yaw_belt skewness_roll_belt skewness_roll_belt.1
## 15699 15395 15413
## skewness_yaw_belt max_roll_belt max_picth_belt
## 15699 15388 15388
## max_yaw_belt min_roll_belt min_pitch_belt
## 15396 15388 15388
## min_yaw_belt amplitude_roll_belt amplitude_pitch_belt
## 15396 15388 15388
## amplitude_yaw_belt var_total_accel_belt avg_roll_belt
## 15396 15388 15388
## stddev_roll_belt var_roll_belt avg_pitch_belt
## 15388 15388 15388
## stddev_pitch_belt var_pitch_belt avg_yaw_belt
## 15388 15388 15388
## stddev_yaw_belt var_yaw_belt gyros_belt_x
## 15388 15388 0
## gyros_belt_y gyros_belt_z accel_belt_x
## 0 0 0
## accel_belt_y accel_belt_z magnet_belt_x
## 0 0 0
## magnet_belt_y magnet_belt_z
## 0 0
```
```r
v_5 <- sapply(select(v_1,names(v_1)[grepl("_arm",names(v_1))]),
function(x) sum(is.na(x)))
v_5
```
```
## roll_arm pitch_arm yaw_arm total_accel_arm
## 0 0 0 0
## var_accel_arm avg_roll_arm stddev_roll_arm var_roll_arm
## 15388 15388 15388 15388
## avg_pitch_arm stddev_pitch_arm var_pitch_arm avg_yaw_arm
## 15388 15388 15388 15388
## stddev_yaw_arm var_yaw_arm gyros_arm_x gyros_arm_y
## 15388 15388 0 0
## gyros_arm_z accel_arm_x accel_arm_y accel_arm_z
## 0 0 0 0
## magnet_arm_x magnet_arm_y magnet_arm_z kurtosis_roll_arm
## 0 0 0 15446
## kurtosis_picth_arm kurtosis_yaw_arm skewness_roll_arm skewness_pitch_arm
## 15448 15398 15445 15448
## skewness_yaw_arm max_roll_arm max_picth_arm max_yaw_arm
## 15398 15388 15388 15388
## min_roll_arm min_pitch_arm min_yaw_arm amplitude_roll_arm
## 15388 15388 15388 15388
## amplitude_pitch_arm amplitude_yaw_arm
## 15388 15388
```
```r
v_7 <- sapply(select(v_1,
names(v_1)[grepl("_forearm",names(v_1))]),
function(x) sum(is.na(x)))
v_7
```
```
## roll_forearm pitch_forearm yaw_forearm
## 0 0 0
## kurtosis_roll_forearm kurtosis_picth_forearm kurtosis_yaw_forearm
## 15448 15449 15699
## skewness_roll_forearm skewness_pitch_forearm skewness_yaw_forearm
## 15447 15449 15699
## max_roll_forearm max_picth_forearm max_yaw_forearm
## 15388 15388 15448
## min_roll_forearm min_pitch_forearm min_yaw_forearm
## 15388 15388 15448
## amplitude_roll_forearm amplitude_pitch_forearm amplitude_yaw_forearm
## 15388 15388 15448
## total_accel_forearm var_accel_forearm avg_roll_forearm
## 0 15388 15388
## stddev_roll_forearm var_roll_forearm avg_pitch_forearm
## 15388 15388 15388
## stddev_pitch_forearm var_pitch_forearm avg_yaw_forearm
## 15388 15388 15388
## stddev_yaw_forearm var_yaw_forearm gyros_forearm_x
## 15388 15388 0
## gyros_forearm_y gyros_forearm_z accel_forearm_x
## 0 0 0
## accel_forearm_y accel_forearm_z magnet_forearm_x
## 0 0 0
## magnet_forearm_y magnet_forearm_z
## 0 0
```
```r
v_8 <- sapply(select(v_1,
names(v_1)[grepl("_dumbbell",names(v_1))]),
function(x) sum(is.na(x)))
v_8
```
```
## roll_dumbbell pitch_dumbbell yaw_dumbbell
## 0 0 0
## kurtosis_roll_dumbbell kurtosis_picth_dumbbell kurtosis_yaw_dumbbell
## 15392 15390 15699
## skewness_roll_dumbbell skewness_pitch_dumbbell skewness_yaw_dumbbell
## 15391 15389 15699
## max_roll_dumbbell max_picth_dumbbell max_yaw_dumbbell
## 15388 15388 15392
## min_roll_dumbbell min_pitch_dumbbell min_yaw_dumbbell
## 15388 15388 15392
## amplitude_roll_dumbbell amplitude_pitch_dumbbell amplitude_yaw_dumbbell
## 15388 15388 15392
## total_accel_dumbbell var_accel_dumbbell avg_roll_dumbbell
## 0 15388 15388
## stddev_roll_dumbbell var_roll_dumbbell avg_pitch_dumbbell
## 15388 15388 15388
## stddev_pitch_dumbbell var_pitch_dumbbell avg_yaw_dumbbell
## 15388 15388 15388
## stddev_yaw_dumbbell var_yaw_dumbbell gyros_dumbbell_x
## 15388 15388 0
## gyros_dumbbell_y gyros_dumbbell_z accel_dumbbell_x
## 0 0 0
## accel_dumbbell_y accel_dumbbell_z magnet_dumbbell_x
## 0 0 0
## magnet_dumbbell_y magnet_dumbbell_z
## 0 0
```
```r
v_9 <- c(names(v_4[v_4 != 0]),
names(v_5[v_5 != 0]),
names(v_7[v_7 != 0]),
names(v_8[v_8 != 0]))
length(v_9)
```
```
## [1] 100
```
```r
#dropping the cols
v_10 <- tbl_df(v_1 %>%
select(-v_9,
-c(X,user_name, raw_timestamp_part_1,
raw_timestamp_part_2, cvtd_timestamp,
new_window,num_window)))
```
```
## Warning: `tbl_df()` is deprecated as of dplyr 1.0.0.
## Please use `tibble::as_tibble()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.
```
```
## Note: Using an external vector in selections is ambiguous.
## i Use `all_of(v_9)` instead of `v_9` to silence this message.
## i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## This message is displayed once per session.
```
```r
v_10$classe <- as.factor(v_10$classe)
v_10[,1:52] <- lapply(v_10[,1:52],as.numeric)
dim(v_10)
```
```
## [1] 15699 53
```
```r
v_11 <- cor(select(v_10, -classe))
diag(v_11) <- 0
v_11 <- which(abs(v_11)>0.8,arr.ind = T)
v_11 <- unique(row.names(v_11))
corrplot(cor(select(v_10,v_11)),
type="upper", order="hclust",method = "number")
```
```
## Note: Using an external vector in selections is ambiguous.
## i Use `all_of(v_11)` instead of `v_11` to silence this message.
## i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## This message is displayed once per session.
```
<img src="practical_ml_files/figure-html/unnamed-chunk-11-1.png" width="960" />
```r
#nfbdyhfgyfhwuiiofjekj
#sjhgfaehfghfgurfhruigherjgheoi
v_12 <- v_10 %>% binarize(n_bins = 4, thresh_infreq = 0.01)
```
```r
v_13<- v_12 %>% correlate(target = classe__A)
v_13%>% plot_correlation_funnel(interactive = T,limits = c(-0.5,0.5))
```
```r
v_15<- v_12 %>% correlate(target = classe__B)
v_15%>% plot_correlation_funnel(interactive = T,limits = c(-0.5,0.5))
```
```r
v_18<- v_12 %>% correlate(target = classe__C)
v_18%>% plot_correlation_funnel(interactive = T,limits = c(-0.5,0.5))
```
```r
v_21<- v_12 %>% correlate(target = classe__D)
v_21%>% plot_correlation_funnel(interactive = T,limits = c(-0.5,0.5))
```
```r
v_23 <- v_12 %>% correlate(target = classe__E)
v_23 %>% plot_correlation_funnel(interactive = T,limits = c(-0.5,0.5))
```
```r
#subseting v_10
v_25 <- c("magnet_arm_x", "pitch_forearm" , "magnet_dumbbell_y",
"roll_forearm", "gyros_dumbbell_y")
v_26<- c("magnet_dumbbell_y", "magnet_dumbbell_x" , "roll_dumbbell" ,
"magnet_belt_y" , "accel_dumbbell_x" )
v_27 <- c("magnet_dumbbell_y", "roll_dumbbell" , "accel_dumbbell_y" ,
"magnet_dumbbell_x", "magnet_dumbbell_z")
v_28 <- c("pitch_forearm" , "magnet_arm_y" , "magnet_forearm_x",
"accel_dumbbell_y", "accel_forearm_x")
v_29 <- c("magnet_belt_y" , "magnet_belt_z" , "roll_belt",
"gyros_belt_z" , "magnet_dumbbell_y")
flsks_cols_qwef <- character()
for(c in c(v_25,v_26,v_27,v_28,v_29)){
flsks_cols_qwef <- union(flsks_cols_qwef, c)
}
v_102 <- v_10 %>% select(flsks_cols_qwef, classe)
```
```
## Note: Using an external vector in selections is ambiguous.
## i Use `all_of(flsks_cols_qwef)` instead of `flsks_cols_qwef` to silence this message.
## i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## This message is displayed once per session.
```
```r
data.frame("arm" = sum(grepl("_arm",flsks_cols_qwef)),
"forearm" = sum(grepl("_forearm",flsks_cols_qwef)),
"belt" = sum(grepl("_belt",flsks_cols_qwef)),
"dumbbell" = sum(grepl("_dumbbell",flsks_cols_qwef)))
```
<div data-pagedtable="false">
<script data-pagedtable-source type="application/json">
{"columns":[{"label":["arm"],"name":[1],"type":["int"],"align":["right"]},{"label":["forearm"],"name":[2],"type":["int"],"align":["right"]},{"label":["belt"],"name":[3],"type":["int"],"align":["right"]},{"label":["dumbbell"],"name":[4],"type":["int"],"align":["right"]}],"data":[{"1":"2","2":"4","3":"4","4":"7"}],"options":{"columns":{"min":{},"max":[10]},"rows":{"min":[10],"max":[10]},"pages":{}}}
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</div>